Abstract:
Techniques are presented for monocular visual simultaneous localization and mapping (SLAM) based on detecting a translational motion in the movement of the camera using at least one motion sensor, while the camera is performing panoramic SLAM, and initializing a three dimensional map for tracking of finite features. Motion sensors may include one or more sensors, including inertial (gyroscope, accelerometer), magnetic (compass), vision (camera) or any other sensors built into mobile devices.
Abstract:
Disclosed are a system, apparatus, and method for multiple client simultaneous localization and mapping. Tracking and mapping may be performed locally and independently by each of a plurality of clients. At configurable points in time map data may be sent to a server for stitching and fusion. In response to successful stitching and fusion to one or more maps known to the server, updated position and orientation information relative to the server's maps may be sent back to the clients. Clients may update their local map data with the received server location data. Clients may receive additional map data from the server, which can be used for extending their maps. Clients may send queries to the server for 3D maps, and the queries may include metadata.
Abstract:
Disclosed are a system, apparatus, and method for monocular visual simultaneous localization and mapping that handles general 6DOF and panorama camera movements. A 3D map of an environment containing features with finite or infinite depth observed in regular or panorama keyframes is received. The camera is tracked in 6DOF from finite, infinite, or mixed feature sets. Upon detection of a panorama camera movement towards unmapped scene regions, a reference panorama keyframe with infinite features is created and inserted into the 3D map. When panoramic camera movement extends toward unmapped scene regions, the reference keyframe is extended with further dependent panorama keyframes. Panorama keyframes are robustly localized in 6DOF with respect to finite 3D map features. Localized panorama keyframes contain 2D observations of infinite map features that are matched with 2D observations in other localized keyframes. 2D-2D correspondences are triangulated, resulting in new finite 3D map features.
Abstract:
Disclosed are a system, apparatus, and method for multiple client simultaneous localization and mapping. Tracking and mapping may be performed locally and independently by each of a plurality of clients. At configurable points in time map data may be sent to a server for stitching and fusion. In response to successful stitching and fusion to one or more maps known to the server, updated position and orientation information relative to the server's maps may be sent back to the clients. Clients may update their local map data with the received server location data. Clients may receive additional map data from the server, which can be used for extending their maps. Clients may send queries to the server for 3D maps, and the queries may include metadata.
Abstract:
A computer-implemented method, apparatus, computer readable medium and mobile device for initializing a 3-Dimensional (3D) map may include obtaining, from a camera, a single image of an urban outdoor scene and estimating an initial pose of the camera. An untextured model of a geographic region may be obtained. Line features from the single image may be extracted and the orientation may be determined with respect to the untextured model and using the extracted line features, the orientation of the camera in 3 Degrees of Freedom (3DOF). In response to determining the orientation of the camera, a translation in 3DOF with respect to the untextured model may be determined using the extracted line features. The 3D map may be initialized based on the determined orientation and translation.
Abstract:
Disclosed are a system, apparatus, and method for monocular visual simultaneous localization and mapping that handles general 6DOF and panorama camera movements. A 3D map of an environment containing features with finite or infinite depth observed in regular or panorama keyframes is received. The camera is tracked in 6DOF from finite, infinite, or mixed feature sets. Upon detection of a panorama camera movement towards unmapped scene regions, a reference panorama keyframe with infinite features is created and inserted into the 3D map. When panoramic camera movement extends toward unmapped scene regions, the reference keyframe is extended with further dependent panorama keyframes. Panorama keyframes are robustly localized in 6DOF with respect to finite 3D map features. Localized panorama keyframes contain 2D observations of infinite map features that are matched with 2D observations in other localized keyframes. 2D-2D correspondences are triangulated, resulting in new finite 3D map features.
Abstract:
Techniques are presented for monocular visual simultaneous localization and mapping (SLAM) based on detecting a translational motion in the movement of the camera using at least one motion sensor, while the camera is performing panoramic SLAM, and initializing a three dimensional map for tracking of finite features. Motion sensors may include one or more sensors, including inertial (gyroscope, accelerometer), magnetic (compass), vision (camera) or any other sensors built into mobile devices.
Abstract:
Exemplary methods, apparatuses, and systems for performing wide area localization from simultaneous localization and mapping (SLAM) maps are disclosed. A mobile device can select a first keyframe based SLAM map of the local environment with one or more received images. A respective localization of the mobile device within the local environment can be determined, and the respective localization may be based on the keyframe based SLAM map. The mobile device can send the first keyframe to a server and receive a first global localization response representing a correction to a local map on the mobile device. The first global localization response can include rotation, translation, and scale information. A server can receive keyframes from a mobile device, and localize the keyframes within a server map by matching keyframe features received from the mobile device to server map features.